A series of tiled models of superficial thickness covering the UK. The models are derived by direct modelling (natural neighbour interpolation) of BGS borehole records and BGS DiGMapGB-50. For the purposes of modelling, superficial deposits include sediments deposited during the Quaternary, subsequent Holocene rivers and coastal systems and also modern anthropogenic material, i.e. deposits that are less than 2.6 million years old. The 50 m x 50 m grids are overprinted with a minimum value so that areas where no bore data is present, but drift is known to occur, are given a minimum 1.5 m thickness. The superficial thickness models have been created as baseline datasets for the BGS Geohazard programme. They represent the first attempt by BGS to create nationwide models of such data and the models provide only a simple, mathematical interpretation of reality. The complexity of superficial deposits in Great Britain is such that it is only possible to model indicative values of thickness and elevation. The models should never be used as a substitute for thorough site investigation. The SDTM comprises three individual datasets; two datasets describe thickness variation and a third dataset details 'proximity' of the modelled data to the original source information. 1. The ASTM (Advanced Superficial Thickness Model) is a model of thickness variation indirectly derived from archive borehole records and map data. 2. The BSTM (Basic Superficial Thickness Model) is a model of thickness variation directly derived from archive borehole records. 3. The DBUFF (distance buffer) dataset is a calculation of spatial distance to the location of any data point used in the model. This provides the user with an indication as to how far the computer has had to interpolate and extrapolate the data from a measured observation point. For more information, refer to the user guide: The National Superficial Deposit Thickness Model (version 5). BGS Open Report OR/09/49. https://webapps.bgs.ac.uk/data/publications/publication.html?id=19867430

This dataset is part of Integrated Hydrometric Units (IHU) of the UK. Hydrometric Areas are used to organise river flow measurement and hydrometric data collection in the UK. Hydrometric Areas are either integral river catchments having one or more outlets to the sea or tidal estuary, or they may include several contiguous river catchments having topographical similarity but separate tidal outlets. In mainland Britain they are numbered from 1 to 97 in clockwise order around the coast commencing in north east Scotland. The larger islands and groups of islands are numbered from 100-108. Ireland has a unified numbering system from 1 to 40 commencing with the River Foyle catchment and circulating clockwise; not all Irish Hydrometric Areas, however, have an outlet to the coast. Only those Hydrometric Areas covering Great Britain and Northern Ireland are included in this dataset. The boundaries between hydrometric areas correspond to catchment boundaries as digitally-derived from CEH Integrated Hydrological Digital Terrain Model (IHDTM) using a catchment definition program. It should be noticed that the Northern Ireland data are clipped to its political boundary so not every Hydrometric Area in this region is completely represented. The naming and numbering convention for the hydrometric areas in Great Britain was originally defined by the Inland Water Survey Committee (and first published in the Surface Water Year-Book of Great Britain 1936-37). For Northern Ireland the system was developed by a multi-agency working group in the 1970s (and first published in Surface Water: United Kingdom 1971-73. Note that full citations of those two publications are provided as additional information source. This dataset represent the same entities as the IHU Hydrometric Areas of the UK without Coastline, however, the outer boundaries of the units follow coastline published by the Ordnance Survey (Meridian 2), rather than the boundaries of the CEH Integrated Hydrological Digital Terrain Model. Full details about this dataset can be found at https://doi.org/10.5285/1957166d-7523-44f4-b279-aa5314163237

This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a at a Miscanthus x. giganteus Greef et Deu (hereafter Miscanthus) plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 4 July 2013 and 25 November 2017. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/71e5b799-fc4d-4a44-8860-a5e358c807fd

The dataset contains the radiocarbon age of soil organic matter fractions collected along grassland-to-forest conversion chronosequences across Scotland. Soil samples were collected in summer 2018. In summer 2019, soil samples were fractionated and the radiocarbon age of bulk soil and soil fraction samples determined by accelerator mass spectrometry. Full details about this dataset can be found at https://doi.org/10.5285/0dd45f6f-0536-4ee3-9932-58bac019d2c6

This dataset presents plant percentage cover by species, average plant cover and species richness for sites along the foredune area of sites distributed between Cape Canaveral (Florida) and Tybee Island (Georgia), USA. Plant cover by species was sampled on three occasions using 0.5 x 0.5m quadrats distributed along 3 transects at up to 28 sites. Observations were conducted in February 2018, July 2018, and January 2019. The coastline was impacted by Hurricane Irma in October 2017 and the data were collected to look at plant composition in coastal foredunes undergoing recovery from the hurricane. The data were collected as part of NERC grant NE/R016593/1, Resilience of a coastal ecosystem following hurricane Irma. Full details about this dataset can be found at https://doi.org/10.5285/100af68f-78e2-4b9d-86b9-5777a5ef38fa

The dataset contains the Diameter at Breast Height (DBH) of trees > 10 cm along with botanical identification (family and species). Data were obtained via forest inventories, in annual campaigns (from 2017 to 2019) conducted in May, with exception of the first campaign, which was from June to November, due to the species identification activity. The research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. The dendrometer dataset contains the distance in circumference (mm) from a window on the dendrometer band installed in the tree and measured with a digital caliper, where that distance changes when the trunk grows. Dendrometric bands data were collected from April 2018 to January 2020. Full details about this dataset can be found at https://doi.org/10.5285/c2587e20-ba4a-4444-8ce9-ccdec15b0aa3

The dataset contains the leaf area index (LAI) (m2/ m2 ) collected with the LAI-2200 C (plant canopy analyzer), that was computed with 5, 4 and 3 rings using the FV2200 software. Additionally, it has the x and y coordinates (m) of the points collected inside the plots and the time of collection (hour: min: sec). This research was collected in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. The campaigns were carried out in October 2017, March 2018, August 2018 and October 2018. Full details about this dataset can be found at https://doi.org/10.5285/6e70665f-b558-4949-b42a-49fbaec7e7cc

The dataset contains stem respiration (ppm) of 320 trees with DBH (Diameter at breast height) > 26 cm, measured with the EGM-4 (Environmental Gas Monitor for CO2). Data were collected on October 2019. In relation to the soil respiration dataset, it contains soil respiration (µmol CO2m-2 s-1) of different type of collars placed on the forest floor, and measured with the LI – 8100 A soil respiration system. Data were collected from June 2017 to October 2019. In both activities, leak tests were done before collections. All research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. Full details about this dataset can be found at https://doi.org/10.5285/591e3708-7ff1-483b-9156-15c721c00daf

The dataset contains the weight of fine root (<2 mm) at two soil depths (0-10 cm and 10-30 cm) collected in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. Data were obtained by the in growth core method, in campaigns conducted every three months from 2017 to 2019 in all plots. Full details about this dataset can be found at https://doi.org/10.5285/b3a55011-bf46-40f5-8850-86dc8bc4c85d

This dataset contains seven month monitoring of weather conditions at Durleigh Reservoir in Somerset, England, during 2018. A Delta T WS-GP1 weather station was installed approximately 4 m above the surface of the reservoir between 5 April and 5 October 2018. Full details about this dataset can be found at https://doi.org/10.5285/dcfa74ce-6d05-4717-978d-e7cdf9b2039e